Multi-dimensional data cubes employ a multi-dimensional indexing scheme to organize large quantities of detailed data. Such detailed data may be associated with any of a variety of subjects, including inventories, sales, manufacturing output, census data, data collected from scientific experiments, social networking statistics, etc. Cells within such data cubes often contain aggregated data (also commonly referred to as “measures”) derived from more detailed data and/or pointers to such detailed data. Often accompanying a data cube is a rule cube having the same size and dimensions as the data cube. There cells within such rule cubes often exist in a one-to-one correspondence with the cells of the data cube, and contain indications of cell rules defining restrictions on access to the corresponding cells of the data cube. Since their inception, data cubes have come to be used to organize increasingly larger quantities of data with ever increasing numbers of dimensions. As a result, the size of the data structures used to represent both the data cubes and corresponding rule cubes have begun to exceed various limitations imposed in various computing devices.